Quality of life (QoL) indicators are now being adopted as clinical outcomes in clinical trials on cancer treatments. Technology-free daily monitoring of patients is complicated, time-consuming and expensive due to the need for vast amounts of resources and personnel. The alternative method of using the patients’ own phones could reduce the burden of continuous monitoring of cancer patients in clinical trials. This paper proposes monitoring the patients’ QoL by gathering data from their own phones. We considered that the continuous multiparametric acquisition of movement, location, phone calls, conversations and data use could be employed to simultaneously monitor their physical, psychological, social and environmental aspects. An open access phone app was developed (Human Dynamics Reporting Service (HDRS)) to implement this approach. We here propose a novel mapping between the standardized QoL items for these patients, the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and define HDRS monitoring indicators. A pilot study with university volunteers verified the plausibility of detecting human activity indicators directly related to QoL.
Vision is a vital cue for human navigation, and it has become in a powerful tool for robot navigation. Computer vision is useful for recognition of positional relationship and relative motion between themselves and objects in the environment. So, we address the problem of navigation for mobile robot in indoor environment. To this task, we tackle the problem using monocular vision, i.e., without other kind of sensors. Insects and some animals use tools as optical flow estimations and time to contact, to their navigation [1]. So, in this paper, we propose a method for obstacle avoidance, without constantly calculating the optical flow field, only it is calculated when the robot is close to colliding with an obstacle, and so, it uses the flow field divergence to decide which direction will should be taken. Physical experiments using a real robot have been conducted in unknown environments.
The contemporary city represents an intellectual challenge that defies intelligence and imagination, its understanding requires breaking down the disciplinary barriers and build a bridge between theoretical and heuristic knowledge, stimulating creativity in the search for methods of observation, measurement, representation and analysis. A constant methodological problem is the lack of models that determine and represent the transversal and longitudinal phenomena that take place in the city, whose unique vision of urbanism, generates a limitation to demonstrate these processes. For this reason, this disciplinary condition generates the need to see trends, concepts, and methodologies of other disciplines that manage the guiding axis of urbanism.The economic development serves as a booster of territorial growth, thus, this link leads to interpret the areas in which economic activities are located and explore how the conformation of the Xalapa city is spatially explained with the help of techniques from other disciplines such as statistics and geography to validate methodological processes.The objective of this work is to show architecture students the proposal of a geostatistical analysis to demonstrate the organization, correlation and spatial association attending to clusters or groups through Cluster Analysis and atypical value, since this geoprocess identifies hot spots, cold spots and spatial outliers that are statistically significant using the "I Anselin local de Morán" statistics. Also, this process allows managing and identifying concentration and dispersion zones that promote the base for the location of vulnerable areas and strategic solutions for economic development and whose methodology can generate urban analyzes of another nature.
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